Autonomous vehicles and various safety/advanced assistance systems rely on sensors and analysis of the data provided by the sensors in order to accurately and precisely perform different functions such as navigating a surrounding environment. That is, the sensors perceive data about the environment which is then interpreted for use in evaluating how to proceed within the environment or perform other actions. As part of perceiving the environment and interpreting the sensor data, a vehicle system perceives and interprets actions, locations, and trajectories associated with objects in the environment such as other vehicles. Moreover, identifying rear indicator signals of nearby vehicles can also assist with anticipating trajectories and dynamic aspects of the nearby vehicles in the environment.
However, accurately detecting and identifying rear indicator signals of a vehicle can encounter various difficulties. One example of a difficulty associated with identifying rear indicator signals involves accurately determining locations of the rear signals. That is, because different makes/models of vehicles can have different configurations of rear signal lights, accurately determining locations and states of the rear signals can be cumbersome. Moreover, further aspects such as the movement of the vehicles, different blinking and/or brake light patterns and other aspects can further add to the difficulties. Consequently, while identifying rear indicator signals of a vehicle is useful when operating the noted systems, the process of identifying the rear indicator signals includes many difficulties which can provide inaccurate results.